Facial expression recognition in educational learning systems

ABSTRACT

Method, systems, and media for participating in and conducting a learning session of a collaborative network. Various embodiments of methods, systems, and media for participating in a learning session of a collaborative network are presented. User image data is received. The user image data is converted into expressive avatar information comprising an avatar identifier and an avatar emotion identifier. The expressive avatar information is transmitted. Altered instructional content is received, wherein the altered instructional content is an alteration of the instructional content and the alteration is based on a plurality of avatar identifiers and a plurality of avatar emotion identifiers, wherein the plurality of avatar identifiers comprises at least the avatar identifier, and wherein the plurality of avatar emotion identifiers comprises at least the avatar emotion identifier. User image data may be converted into expressive avatar data using facial expression recognition techniques.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationSer. No. 61/728,989, filed on Nov. 21, 2012, which is herebyincorporated by reference herein in its entirety.

BACKGROUND

The present invention relates to dissemination of education material ingeneral, and to methods, systems, and media of developing sucheducational materials through an online collaboration environment.

With developments in the education industry, students seek access tocourse-related information and their own course work, anywhere, anytime.Student want current, relevant, interesting and engaging coursematerials and assignments taught by teachers, instructors, counselorsand advisors who are aware of student's educational and professionalpath and goals based on a clear map of course progress and degreeprogram. Enabling and facilitating students' online activities aroundtheir campus is a major consideration in providing the desired studentexperience.

Online education now demands providing educational services to a diverseglobal audience from different cultural backgrounds. Education providersface the challenge of providing high quality education across a diversestudent population. Educational programs must provide skills thatstudents can apply in their lives and professions to make a realdifference in the real world. Educators must strive to create acommunity of learners connected to one another.

A learning management system (LMS), as referred to in the art, issoftware for delivering, tracking and managing training of students.LMSs range from systems for managing student training records tosoftware for distributing courses over the Internet and offeringfeatures for online collaboration. In many instances, LMSs are used toautomate record-keeping as well as to register students for classroomand online courses. Self-registration, faculty-led learning, learningworkflow, the provision of on-line learning (e.g., read and understand),on-line assessment, management of continuous professional education(CPE), collaborative learning (e.g., application sharing, discussionthreads), and learning resource management (e.g., instructors,facilities, equipment), are various aspects of LMSs.

FIG. 1 is a diagram depicting a known LMS 10, including one offered byBlackboard, WebCT, Moodle, eCollege and others, which allows a facultymember to place his or her courses, in whole or in part, online. Asdepicted, the faculty 12 plays a central role for mediating between astudent 13, presenting course content 15 and assessing a student 14.LMSs 10 usually provide all-inclusive learning environments for facultyand students, with the faculty 12 disseminating instructional materialspecific to a course of study amongst students. As such, the facultymember serves as the facilitator, assessor and content developer.

Conceptually, there is no difference between the role of a teacher inconventional LMSs 10 and the role of a teacher in a bricks and mortarclassroom. In both cases, the students are grouped and assigned aspecific teacher. The teacher introduces all course content andmaterials into the classroom and mediates and assesses the learningprocess of the student. Thus, under LMS 10, the web is a tool toreplicate, as closely as possible, the traditional classroom environmentand the LMS 10 is limited by its system boundaries, just as the physicalclassroom is limited by four walls and doors.

With advances in content and media delivery technologies, the LMS modelhas not fully taken advantage of the available features for educatingstudents. For example, such advances allow students to accesseducational content not only via laptops and desktops, but also smartphones, PDA's, iPods, Netbooks and eBooks. It is, for example, estimatedthat the majority of prospective student market has a smart phone orPDA, with advances content delivery capabilities via downloadableapplications or by content streaming. These new devices have enabledusers access to podcasting, wikis, blogs, web cams, eBook readers, MP3players, social networks and virtual learning environments.

Conventional LMS developers' attempt in incorporating new features intotheir existing systems in some cases can result in significantdevelopments cost in redesigning their content to incorporate thefunctionality of these new technologies. In other cases, the developersmay have to open up their system platform through applicationprogramming interfaces (API's) to “bolt on” new technologicalcapabilities. LMS redesign investment may be expensive, especially whennew development work may not be able to keep up with the proliferationof ever advancing technologies and features. Opening up platformsthrough APIs may present a significant competitive disadvantage to LMSvendors and service providers who have invested heavily in theirproprietary instructional material delivery systems.

Additionally, educational services are increasingly offered over globalnetworks of institutions and universities. For example, LaureateEducation Inc., the assignee of the present application, currentlyoffers accredited campus-based and online courses in a wide variety ofprograms, including undergraduate and graduate degree programs andspecializations, to nearly a wide range of students in numerouscountries. Such a global educational network requires supportinglearning environments that are tailored to bring to students a globalperspective blended with a local point of view, creating a trulymulticultural, career-oriented educational experience for students. Forexample, the educational experience may be a career-focused or licensingprogram, a multi-year undergraduate degree program, or master's and/ordoctorate degree program in any one of a number of fields includingengineering, education, business, health care, hospitality,architecture, and information technology, etc.

Laureate Education Inc.'s U.S. Patent Publication No. US 2009-0291426A1, the entire contents of which are hereby incorporated by reference,discloses an “Educational System For Presenting One Or More LearningUnits To Students In Different Learning Environments”, where each unitis associated with an assessment information relating to students. Adigital rights and asset management application controls access to thecontent associated with each one of said one or more units according tocorresponding unit identifiers. An assessment application, e.g., a gradebook application, stores assessment information derived from presentingthe content to said one or more users in the first and secondinteractive environments, with the unit identifier correlating theassessment information with the units.

Laureate Education Inc.'s U.S. Patent Publication No. 2009-0311658 A1,the entire contents of which are hereby incorporated by reference,discloses “System And Method For Collaborative Development Of OnlineCourses And Programs Of Study” over a social network. A database storesan initial framework that defines a sequence of learning units forcreating a desired learning environment for students. The learning unitsare identified by corresponding learning unit identifiers. A pluralityof workstations coupled to the network are used for entry of reviewerinformation by the participants using the learning environment createdfor the students. The reviewer information comprise one or more commentsentered by one participant about a learning unit and a rank entered byanther participant about the comment, with the rank being correlatedwith a defined ranking standard. A processor processes the rankaccording to a predefined criteria to produce a ranking result that isassociated with a learning unit identifier. The ranking result is usedfor associating learning content to the learning unit identified by thelearning unit identifier.

The conventional learning process also involves receiving and respondingto facial expressions from students. A facial expression is a visiblemanifestation of the affective state, cognitive activity, intention,personality, and psychopathology of a person. Facial expressions conveynon-verbal cues and play an important role in the instructional setting.These cues may indicate that the student is perplexed, bored, excited,happy, thoughtful, frustrated, or a wide range of other emotions.Instructors in the conventional learning process use these cues asfeedback and adapt lessons accordingly to meet their students' needs.

Also known are facial recognition software systems (FRSS). The paper“Facial Expression Recognition: A Brief Tutorial Overview” by Chibelushiand Bourel, the entire contents of which are hereby incorporated byreference, provides an overview of FRSS. Although humans recognizefacial expressions virtually without any effort or dealy, reliableexpression recognition by machines is still a challenge. Severaldifferent approaches are known to overcome these challenges. Theseapproaches include those described by U.S. Pat. No. 6,690,814 B1 toYuasa et al., the entire contents of which are hereby incorporated byreference, and the article “Spontaneous Emotional Facial ExpressionDetection” by Zeng et al., Journal of Multimedia, Vol. 1, No. 5, August2006, the entire contents of which are hereby incorporated by reference.

FIG. 2 illustrates a logic flow diagram depicting a known process forclassifying facial expressions. The process in the FRSS 200 begins byacquiring an image 200. The image may be acquired from an input device,and the input device may be a camera, a video recorder, an integratedcamera, a file, a streaming video source, a computer, a portablecomputer, a mobile device, a phone, or any other source capable ofsupplying an image. The image may be in the form of raw data 220. Theimage may be user image data 215. Pre-processing 230 may be performed onthe raw data 220 to perform face segmentation. An example of facesegmentation is shown in element 235. After pre-processing 235, featureextraction 240 may be performed, which converts pixel data in ahigher-level representation, for example, shape, motion, color, texture,or spatial configuration of the face or its components. The extractedfeatures are represented by feature vector 242, which includes basisvectors 244 and weights 246. Feature data may include feature vector242, basis vectors 244, or weights 246. Classification 250 may beperformed on the feature vector 242. Classification 250 uses a model 255to determine which emotion 257 is present in the image. Post-processing260 may be performed on the output from the classifications 250.Post-processing uses techniques to improve recognition and includestechniques of exploiting domain knowledge to correct classificationerrors or coupling together several levels of classification hierarchy.The process in FRSS 200 produces an emotion value 270.

Also known are avatars. As used herein, an avatar is the graphicalrepresentation of the user or the user's alter ego or character. It maytake either a three-dimensional form, as in games or virtual worlds, ora two-dimensional form as an icon in Internet forums and other onlinecommunities. It can also refer to a text construct. An avatar is anobject representing the user. An avatar may be as simple as a smileyface or as complex as a virtual face. U.S. Pat. No. 7,751,599 B2 to Chenet al., the contents of which are hereby incorporated by reference,describes performing facial recognition to and converting the facialrecognition into avatars.

With advances in information technologies, there exists a need for aneducational system that can easily implement advances in learningtechnology for responding to users' facial expressions during thepresentation of course content.

BRIEF SUMMARY

Various embodiments are generally directed to methods, systems, andmedia for participating in a learning session of a collaborativenetwork. User image data is received. The user image data is convertedinto expressive avatar information comprising an avatar identifier andan avatar emotion identifier. The expressive avatar information istransmitted. Altered instructional content is received, wherein thealtered instructional content is an alteration of the instructionalcontent and the alteration is based on a plurality of avatar identifiersand a plurality of avatar emotion identifiers, wherein the plurality ofavatar identifiers comprises at least the avatar identifier, and whereinthe plurality of avatar emotion identifiers comprises at least theavatar emotion identifier.

Various embodiments are generally directed to methods, systems, andmedia for conducting a learning session over a collaborative network.Expressive avatar information associated with instructional content isreceived from a plurality of participant workstations, the expressiveavatar information comprising a plurality of avatar identifiers and aplurality of avatar emotion identifiers. Instructional content isaltered based on the plurality of avatar identifiers and the pluralityof avatar emotion identifiers. The altered instructional content istransmitted to the plurality of participant workstations.

These and other features and advantages will be apparent from a readingof the following detailed description and a review of the associateddrawings. It is to be understood that both the foregoing generaldescription and the following detailed description are explanatory onlyand are not restrictive of aspects as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a diagram depicting a known learning managementsystem.

FIG. 2 illustrates a logic flow diagram depicting a known process forclassifying facial expressions.

FIG. 3 illustrates a block diagram of an educational system that usesavatars in accordance with one or more embodiments.

FIG. 4 illustrates a block diagram of a network having a front-endsystem and a back-end system in accordance with one or more embodiments.

FIG. 5A illustrates a table of emotion values and avatar expressionidentifiers in accordance with one or more embodiments.

FIG. 5B illustrates a set of exemplary avatar images in accordance withone or more embodiments.

FIG. 6 illustrates an instructor interface in accordance with one ormore embodiments.

FIG. 7 illustrates an instructor interface in accordance with one ormore embodiments.

FIG. 8 illustrates a block diagram in accordance with one or moreembodiments.

FIG. 9 illustrates a block diagram in accordance with one or moreembodiments.

FIG. 10 illustrates a logic flow diagram in accordance with one or moreembodiments.

DETAILED DESCRIPTION OF THE DRAWINGS

The conventional systems discussed herein are unsatisfactory for anumber of reasons. Transmitting video or image files over networksconsumes a large amount of bandwidth because video and image files ofpeople are typically quite large. For example, uncompressed video withthe resolution of 720×486 pixels at 29.97 frames per second with 8 bitpixel encoding requires about 20 MB per second to transmit, or 70 GB perhour. An online course with 100 users would require around 7000 GB perhour. As a result, conventional LMS do not allow instructors to leveragethe non-verbal cues present in facial expressions because the bandwidthrequired to transmit video or image files over networks does not scaleto large numbers of users and becomes too prohibitive. This is evidentwith systems with smaller class sizes around 100 users.

Embodiments attempt to solve these problems by taking a differentapproach to transmitting facial expression information in a LMS. Imagedata of the users interacting with the LMS is received and convertedinto avatar information. Facial expression recognition is performed onthe image data to determine the emotion or facial expression present ona user's face. The expression is represented by an avatar emotionidentifier, and the user's avatar is identified by an avatar identifier.The expressive avatar information includes the avatar emotion identifierand the avatar identifier. The expressive avatar information may berepresented using much less data than video, e.g., a byte or less foreach data point, and may only need to be transmitted when the avatar orexpression changes.

FIG. 3 is a block diagram of one embodiment of an educational systemthat uses expressive avatar information for educational courses.According to the present invention, the courses instructional contentthat is may be altered based on the received expressive avatarinformation. In this embodiment, users 1-n are registered within aparticular learning system or institution and may connect to a network(i.e. the Internet) through a mobile device, for example, a PDA, an iPador a laptop computer. A server, maintained by the school/university or athird party vendor, may include an inventory of all users that areaffiliated with the particular learning program or institution. In oneembodiment, such users are associated with network address, e.g., IPaddresses, that may be stored in a user's profile. When a user accessesthe LMS through their device receives user image data from the user. Theuser image data may be received through an input device. The inputdevice may be a camera, video recorder, an integrated camera, a file, astreaming video source, a computer, a portable computer, a mobiledevice, or a phone. The user device converts the user image data intoexpressive avatar information. The expressive avatar information is sentto the server. In one embodiment, the server may have access to one ormore avatar databases that store expressive avatar information. Theserver may send the expressive avatar information for any or all of theusers to device 2, and device 2 may display any or all of the avatarimages corresponding to the expressive avatar information.

FIG. 4 shows the block diagram of a network having a front-end systemand a back-end system. The front-end system 330 includes a firewall 332,which is coupled to one or more load balancers 334 a, 334 b. Loadbalancers 334 a-b are in turn coupled to one or more web servers 336a-b. To provide online learning sessions, the web servers 336 a-b arecoupled to one or more application servers 338 a-c, each of whichincludes and/or accesses one or more front-end databases 340, 342, whichmay be central or distributed databases. The application servers servevarious modules used for interaction between the different users and thelearning system, including instructional enrolment module, courseregistration module, learning session management module, contentdelivery module, avatar module, proximity module and event module. Theavatar module allows a student and/or teacher to interact withinstructional content based expressive avatar information. The proximitymodule allows a teacher and/or students to interact with one anotherbased on geographic proximity. The event module allows a teacher and/orstudent to interact with instructional material based on a geographicalevent. These modules may be run independently of each other based oncorresponding teacher, student, geolocation and event profiles, asfurther described below.

Web servers 336 a-b provide various user portals, including student,teacher, and event portals. The servers 336 a-b are coupled to loadbalancers 334 a-b, which perform load balancing functions for providingoptimum online session performance by transferring client user requeststo one or more of the application servers 338 a-c according to a seriesof semantics and/or rules. The application servers 338 a-c may include adatabase management system (DBMS) 346 and/or a file server 348, whichmanage access to one or more databases 340, 342. In the exemplaryembodiment depicted in FIG. 4, the application servers 338 a and/or 338b provide instructional content to the users 306, 310 which includeelectronic interfaces, progress reports, student profiles, teacherprofiles, event profiles, as well as instructional content correlatedwith a student, teacher, course, school, expressive avatar informationor event as processed by the server. Some of the instructional contentis generated via code stored either on the application servers 338 aand/or 338 b, while some other information and content, such as studentprofiles, instructional material, teacher schedule, or otherinformation, which is presented dynamically to the user, is retrievedalong with the necessary data from the databases 340, 342 viaapplication server 338 c. The application server 338 b may also provideusers 306, 306 access to executable files which can be downloaded andinstalled on user devices 304, 310 for creating an appropriate learningenvironments and sessions, with branding and or marketing features thatare tailored for a particular application, client or customer.

The central or distributed database 340, 342, stores, among otherthings, the web content and instructional material deliverable to thestudents. The avatar database 340, 342 also stores retrievableinformation relating to or associated with students, teachers,responsible authorities, parents, learning centers, profiles (student,facilitator, teacher, faculty, course developer, assessor, etc.),billing information, schedules, statistical data, attendance data,enrollment data, teacher attributes, student attributes, historicaldata, demographic data, compliance data, certification data, billingrules, third party contract rules, educational district requirements,expressive avatar information, etc. Any or all of the foregoing data canbe processed and associated as necessary for achieving a desiredlearning objective or a business objective associated with operating thesystem of the present invention.

Updated program code and data are transferred from the back-end system360 to the front-end system 330 to synchronize data between databases340, 342 of the front-end system and databases 340 a, 342 a of theback-end system. Further, web servers 336 a, 336 b, which may be coupledto application servers 338 a-c, may also be updated periodically via thesame process. The back-end system 360 interfaces with a user device 350such as a workstation, enabling interactive access for a system user352, who may be, for example, a developer or a system administrator. Theworkstation 350 may be coupled to the back-end system 360 via a localnetwork 328. Alternatively, the workstation 350 may be coupled to theback-end system 360 via the Internet 120 through the wired network 324and/or the wireless network 326.

The back-end system 360 includes an application server 362, which mayalso include a file server or a database management system (DBMS). Theapplication server 362 allows a user 352 to develop or modifyapplication code or update other data, e.g., electronic content andelectronic instructional material, in databases 340 a, 342 a. Accordingto one embodiment, interactive client-side applications on the internetexecute on a variety of internet delivery devices such as a web-browser,smart phones, and tablet devices such as the iPad, to provide animproved core student experience.

FIG. 5A illustrates a table of emotion values and avatar expressionidentifiers in accordance with one or more embodiments. Each emotionvalue corresponds the avatar expression identifier in the same row.Several emotion labels may correspond to the same avatar expressionidentifier.

FIG. 5B illustrates a set of exemplary avatar images in accordance withone or more embodiments. The avatar images may take either athree-dimensional form, as in games or virtual worlds, or atwo-dimensional form as an icon in Internet forums and other onlinecommunities. It can also refer to a text construct. An avatar image isan object representing the user. The avatar image may be as simple as asmiley face as shown in FIG. 5 or as complex as a virtual face.

FIG. 6 illustrates an instructor interface in accordance with one ormore embodiments.

In one embodiment, the instructor interface includes a currentinstructional content display, an avatar status display, and an actioninterface element associated with an action. The instructional contentis displayed in the current instructional content display. When thecontent is altered, the altered content may be displayed in the currentinstructional content display in response to the alteration. The avatarstatus display lists the avatar images for a plurality of students thatare viewing the content presented in the current instructional contentdisplay. Each avatar image may have the name of a user or an identifierof a user to let the instructor know which user avatar image correspondsto which user. The avatar status display may also include a graph thatindicates changes of avatar images over the course of the presentationof course content. The action interface element may comprise a button orany other input element on the interface. The actions that correspond tothe action interface element include pausing display of the contentpresented in the current instructional content display, stopping displayof the content presented in the current instructional content display,replacing the content presented in the current instructional contentdisplay with other instructional content, inserting additionalinstructional content into the content presented in the currentinstructional content display, or any combination thereof. The interfacemay include any number of action interface elements that may correspondto any combination of actions. When the user performs an action, thesystem transmits the altered content to the other users of the system.The altered content may be selectively transmitted to all or some of theother users on the system.

In one embodiment the instructor interface 600 may also include asuggestion request interface element. When a user selects the suggestionrequest interface element, the system may provide the user with asuggested action. The suggestion may be any action or combination ofactions that the system can take described above. The suggestion may bebased on analysis of the expressive avatar information of the pluralityof users. The system may compare the expressive avatar information to amodel. The model may a simple model that merely counts the number ofusers have avatar emotion identifiers of each type. In this simplemodel, the threshold is the number avatar emotion identifier that is thehighest of all avatar emotion identifiers. The threshold is exceeded bythe avatar emotion identifier that has the most users. For example, ifeveryone has an avatar emotion identifier corresponding to happy, thesystem may alter the instructional content by performing an actionassociated with happy meeting the threshold. The model may based on morecomplicated machine learning or artificial intelligence techniques,including Bayesian learning techniques, artificial neural networks,kernel machines, genetic algorithms, rule-based learning techniques, orany other techniques currently known in the art. The suggested action isprovided to the user of the instructional interface. The user take thesuggestion and perform the suggest action to alter the content or theuser may disregard the suggestion.

The instructor interface 600 may also include an automatic adjustinginterface element. When a user selects the automatic adjusting interfaceelement, the system determines a suggested action as described abovewith respect to the suggestion request interface element. However,instead of providing the suggestion to the user and waiting for aresponse to perform the action, the system performs the determinedaction without further user interaction. The system may continue toperform alterations to the instructional content during thepresentation, or the system may only perform one action in response toselection of the automatic adjusting interface element. Alternatively,the system may continue to perform alterations until the expiration of atime period. The time period may be set by a user, configured by anotheruser in the system, or determined by the machine.

FIG. 7 illustrates an instructor interface 700 in accordance with one ormore embodiments. Instructor interface is similar instructor interface600, except instructor interface 700 shows a configuration of the avatarstatus display. The avatar status display includes avatar images thatrepresent the different types of avatar emotion identifiers. Next toeach avatar image is the total number of users currently displaying afacial expression corresponding to the particular avatar emotionidentifier. The graphs track the changes in the number of users for eachavatar emotion identifier over the course of the presentation of coursecontent. The instructor interface 600 and instructor interface 700 mayinclude any combination of the displays and elements discussed herein.

FIG. 8 illustrates a block diagram in accordance with one or moreembodiments. The user operating a device interacts with the studentinterface. An input device of the device receives user image data. Theuser image data is converted into expressive avatar information. Theexpressive avatar information is transmitted through the network toanother user's interface on the other user's device and represented onthe other user's interface as an avatar image.

FIG. 9 illustrates a block diagram in accordance with one or moreembodiments. A plurality of user image data is converted into expressiveavatar information. A plurality of the expressive avatar information istransmitted through the network. The device receives the plurality ofexpressive avatar information.

FIG. 10 a logic flow diagram in accordance with one or more embodiments.At block 1010, a user image is received. At block 1030, the user imageis converted to expressive avatar information. At block 1050, expressiveavatar information is transmitted. At block 1070, expressive avatarinformation is received. At block 1090, instructional content is alteredbased on the expressive avatar information.

Numerous specific details have been set forth to provide a thoroughunderstanding of the embodiments. It will be understood, however, thatthe embodiments may be practiced without these specific details. Inother instances, well-known operations, components and circuits have notbeen described in detail so as not to obscure the embodiments. It can beappreciated that the specific structural and functional details arerepresentative and do not necessarily limit the scope of theembodiments.

Various embodiments may comprise one or more elements. An element maycomprise any structure arranged to perform certain operations. Eachelement may be implemented as hardware, software, or any combinationthereof, as desired for a given set of design and/or performanceconstraints. Although an embodiment may be described with a limitednumber of elements in a certain topology by way of example, theembodiment may include more or less elements in alternate topologies asdesired for a given implementation.

It is worthy to note that any reference to “one embodiment” or “anembodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment. The appearances of the phrase “in oneembodiment” in the specification are not necessarily all referring tothe same embodiment.

Although some embodiments may be illustrated and described as comprisingexemplary functional components or modules performing variousoperations, it can be appreciated that such components or modules may beimplemented by one or more hardware components, software components,and/or combination thereof. The functional components and/or modules maybe implemented, for example, by logic (e.g., instructions, data, and/orcode) to be executed by a logic device (e.g., processor). Such logic maybe stored internally or externally to a logic device on one or moretypes of computer-readable storage media.

Some embodiments may comprise an article of manufacture. An article ofmanufacture may comprise a storage medium to store logic. Examples of astorage medium may include one or more types of computer-readablestorage media capable of storing electronic data, including volatilememory or non-volatile memory, removable or non-removable memory,erasable or non-erasable memory, writeable or re-writeable memory, andso forth. Examples of storage media include hard drives, disk drives,solid state drives, and any other tangible storage media.

It also is to be appreciated that the described embodiments illustrateexemplary implementations, and that the functional components and/ormodules may be implemented in various other ways which are consistentwith the described embodiments. Furthermore, the operations performed bysuch components or modules may be combined and/or separated for a givenimplementation and may be performed by a greater number or fewer numberof components or modules.

Unless specifically stated otherwise, it may be appreciated that termssuch as “processing,” “computing,” “calculating,” “determining,” or thelike, refer to the action and/or processes of a computer or computingsystem, or similar electronic computing device, that manipulates and/ortransforms data represented as physical quantities (e.g., electronic)within registers and/or memories into other data similarly representedas physical quantities within the memories, registers or other suchinformation storage, transmission or display devices.

Some of the figures may include a flow diagram. Although such figuresmay include a particular logic flow, it can be appreciated that thelogic flow merely provides an exemplary implementation of the generalfunctionality. Further, the logic flow does not necessarily have to beexecuted in the order presented unless otherwise indicated. In addition,the logic flow may be implemented by a hardware element, a softwareelement executed by a processor, or any combination thereof.

While certain features of the embodiments have been illustrated asdescribed above, many modifications, substitutions, changes andequivalents will now occur to those skilled in the art. It is thereforeto be understood that the appended claims are intended to cover all suchmodifications and changes as fall within the true spirit of theembodiments.

1. A method for participating in a learning session over a collaborativenetwork, the method comprising: receiving user image data, wherein theuser image data is associated with a time during a presentation ofinstructional content; converting the user image data into expressiveavatar information, the expressive avatar information comprising anavatar identifier and an avatar emotion identifier; transmitting theexpressive avatar information; and receiving altered instructionalcontent, wherein the altered instructional content is an alteration ofthe instructional content and the alteration is based on a plurality ofavatar identifiers and a plurality of avatar emotion identifiers,wherein the plurality of avatar identifiers comprises at least theavatar identifier, and wherein the plurality of avatar emotionidentifiers comprises at least the avatar emotion identifier.
 2. Themethod of claim 1, wherein converting the user image data intoexpressive avatar information further comprises: analyzing the userimage data to produce feature data; classifying the feature data toproduce an emotion value; assigning the emotion value to the avataremotion identifier; and associating the avatar emotion identifier withthe avatar identifier.
 3. The method of claim 1, wherein receiving userimage data further comprises: receiving the user image data from aninput device, the input device comprising a camera, a video recorder, anintegrated camera, a file, a streaming video source, a computer, aportable computer, a mobile device, or a phone.
 4. The method of claim 1further comprising: receiving second expressive avatar informationassociated with the presentation of instructional content from aplurality of participant workstations, the second expressive avatarinformation comprising a second plurality of avatar identifiers and asecond plurality of avatar emotion identifiers; presenting a studentinterface comprising an avatar status display; determining a pluralityof avatar images based on the second plurality of avatar identifiers andthe second plurality of avatar emotion identifiers; and displaying theplurality of avatar images in the avatar status display.
 5. A method forconducting a learning session over a collaborative network, the methodcomprising: receiving expressive avatar information associated with apresentation of instructional content from a plurality of participantworkstations, the expressive avatar information comprising a pluralityof avatar identifiers and a plurality of avatar emotion identifiers;altering the instructional content based on the plurality of avataridentifiers and the plurality of avatar emotion identifiers; andtransmitting the altered instructional content to the plurality ofparticipant workstations.
 6. The method of claim 5, wherein altering theinstructional content further comprises: comparing the plurality ofavatar identifiers and the plurality of avatar emotion identifiers to amodel; determining whether the expressive avatar information exceeds athreshold of the model; and if the expressive avatar information exceedsthe threshold, altering the instructional content by performing anaction associated with the threshold.
 7. The method of claim 5 furthercomprising: presenting an instructor interface, the instructor interfacecomprising a current instructional content display, an avatar statusdisplay, and an action interface element associated with an action;displaying the instructional content in the current instructionalcontent display; determining a plurality of avatar images based on theplurality of avatar identifiers and the plurality of avatar emotionidentifiers; displaying the plurality of avatar images in the avatarstatus display; receiving a selection of the action interface element;and wherein altering the instructional content further comprisesaltering the instructional content by performing the action associatedwith the action interface element on the instructional content.
 8. Themethod of claim 7 further comprising: displaying a suggestion requestinterface element on the instructor interface; receiving a selection ofthe suggestion request interface element; and providing a suggestedaction to alter the instructional content.
 9. The method of claim 5,wherein altering the instructional content further comprises: pausingdisplay of the instructional content; stopping display of theinstructional content; replacing the instructional content with a secondinstructional content; or inserting additional instructional contentinto the instructional content.
 10. A system for participating in alearning session over a collaborative network, the system comprising: aprocessor configured to: receive user image data, wherein the user imagedata is associated with a time during a presentation of instructionalcontent; convert the user image data into expressive avatar information,the expressive avatar information comprising an avatar identifier and anavatar emotion identifier; transmit the expressive avatar information;receive altered instructional content, wherein the altered instructionalcontent is an alteration of the instructional content and the alterationis based on a plurality of avatar identifiers and a plurality of avataremotion identifiers, wherein the plurality of avatar identifierscomprises at least the avatar identifier, and wherein the plurality ofavatar emotion identifiers comprises at least the avatar emotionidentifier.
 11. The system of claim 10, wherein the processor is furtherconfigured to: analyze the user image data to produce feature data;classify the feature data to produce an emotion value; assign theemotion value to the avatar emotion identifier; and associate the avataremotion identifier with the avatar identifier.
 12. The system of claim10, wherein the processor is further configured to: receive the userimage data from an input device, the input device comprising a camera, avideo recorder, an integrated camera, a file, a streaming video source,a computer, a portable computer, a mobile device, or a phone.
 13. Thesystem of claim 10, wherein the processor is further configured to:receive second expressive avatar information associated with thepresentation of instructional content from a plurality of participantworkstations, the second expressive avatar information comprising asecond plurality of avatar identifiers and a second plurality of avataremotion identifiers; present a student interface comprising an avatarstatus display; determine a plurality of avatar images based on thesecond plurality of avatar identifiers and the second plurality ofavatar emotion identifiers; and display the plurality of avatar imagesin the avatar status display.
 14. A system for conducting a learningsession over a collaborative network, the system comprising: a processorconfigured to: receive expressive avatar information associated with apresentation of instructional content from a plurality of participantworkstations, the expressive avatar information comprising a pluralityof avatar identifiers and a plurality of avatar emotion identifiers;alter the instructional content based on the plurality of avataridentifiers and the plurality of avatar emotion identifiers; andtransmit the altered instructional content to the plurality ofparticipant workstations.
 15. The system of claim 14, wherein theprocessor is further configured to: compare the plurality of avataridentifiers and the plurality of avatar emotion identifiers to a model;determine whether the expressive avatar information exceeds a thresholdof the model; and alter the instructional content by performing anaction associated with the threshold if the expressive avatarinformation exceeds the threshold.
 16. The system of claim 14, whereinthe processor is further configured to: present an instructor interface,the instructor interface comprising a current instructional contentdisplay, an avatar status display, and an action interface elementassociated with an action; display the instructional content in thecurrent instructional content display; determine a plurality of avatarimages based on the plurality of avatar identifiers and the plurality ofavatar emotion identifiers; display the plurality of avatar images inthe avatar status display; receive a selection of the action interfaceelement; and wherein altering the instructional content furthercomprises altering the instructional content by performing the actionassociated with the action interface element on the instructionalcontent.
 17. The system of claim 16, wherein the processor is furtherconfigured to: display a suggestion request interface element on theinstructor interface; receive a selection of the suggestion requestinterface element; and provide a suggested action to alter theinstructional content.
 18. The system of claim 14, wherein the processoris further configured to: pause display of the instructional content;stop display of the instructional content; replace the instructionalcontent with a second instructional content; or insert additionalinstructional content into the instructional content.
 19. A computerreadable storage medium comprising instructions that if executed enablea computing system to: receive user image data, wherein the user imagedata is associated with a time during a presentation of instructionalcontent; convert the user image data into expressive avatar information,the expressive avatar information comprising an avatar identifier and anavatar emotion identifier; transmit the expressive avatar information;receive altered instructional content, wherein the altered instructionalcontent is an alteration of the instructional content and the alterationis based on a plurality of avatar identifiers and a plurality of avataremotion identifiers, wherein the plurality of avatar identifierscomprises at least the avatar identifier, and wherein the plurality ofavatar emotion identifiers comprises at least the avatar emotionidentifier.
 20. A computer readable storage medium comprisinginstructions that if executed enable a computing system to: receiveexpressive avatar information associated with a presentation ofinstructional content from a plurality of participant workstations, theexpressive avatar information comprising a plurality of avataridentifiers and a plurality of avatar emotion identifiers; alter theinstructional content based on the plurality of avatar identifiers andthe plurality of avatar emotion identifiers; transmit the alteredinstructional content to the plurality of participant workstations.